CN104025561A - Image compression method and image processing apparatus - Google Patents
Image compression method and image processing apparatus Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/136—Incoming video signal characteristics or properties
- H04N19/14—Coding unit complexity, e.g. amount of activity or edge presence estimation
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
- H04N19/103—Selection of coding mode or of prediction mode
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
- H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
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Abstract
The present invention provides an image compression method and an image processing apparatus. The image compression method comprises: dividing an original image into at least one image block; determining a number of color types contained in image data corresponding to each image block; for image blocks whose number of color types is less than or equal to a first threshold, performing compression using a lossless compression algorithm, and obtaining code streams after compression; for image blocks whose number of color types is greater than the first threshold, performing compression using a lossy compression algorithm, and obtaining code streams after compression; combining the code streams obtained after compressing the at least one image block into a unified code stream; and sending the unified code stream to a client. By distinguishing image block types according to the number of color types of each image block, and using the lossy compression algorithm or the lossless compression algorithm to perform encoding compression on image blocks of different types, the present invention can effectively give consideration to reconstruction quality and compression efficiency of a desktop image.
Description
The present invention relates to computer technology, more particularly to a kind of method for compressing image and image processing apparatus for method for compressing image and image processing apparatus technical field.Background technology
At present, Desktop Share technology is often applied to the fields such as telecommuting, multimedia conferencing, multimedia teaching.Because Desktop Share technology is increasingly ripe, to the less demanding of terminal device, especially under the fast-developing background of wireless communication technology, various handheld terminals and based on 3G (Third Generation) Moblie (3rd-generation, network equipment 3G) can also share the desktop of remote server so that Desktop Share technology has obtained more being widely applied.
Existing Desktop Share technology directly can carry out screenshot capture in server end, and the interface function provided by operating system obtains the raw information of desktop picture, but the data volume of computer desktop image is very huge.For example, one frame desktop picture data of 17 cun of liquid crystal displays are 3.75MB, if intercepting desktop picture with the speed of 15 frames/second, the data volume then produced for 1 second is 56.25MB, when such data volume is transmitted on current 10M/100M even 1000M internet, easily cause network congestion and transmission delay, it is therefore desirable to carry out effective compressed encoding, the desktop picture sequence after being compressed to desktop picture before real-time Transmission desktop picture.Desktop picture sequence after compression is sent to client by server, and client is decoded to the desktop picture sequence received, so as to obtain the desktop picture of server.
Typical compression algorithm includes Lossy Compression Algorithm and lossless compression algorithm.Lossy Compression Algorithm such as Joint Photographic Experts Group（Joint Photographic Experts Group, JPEG) algorithm etc., with higher compression ratio, but need to lose picture quality as cost, ambiguous situation occurs in word especially in image, and Lossy Compression Algorithm is not particularly suited for some special application scenarios.The generation of situations such as example in medical industry in order to avoid judging by accident, does not allow to would detract from compression algorithm to apply in Desktop Share.Lossless compression algorithm such as run length encoding (Run- Length Encoding, RED algorithms, LZW (Lempel-Ziv- Welch Encoding) algorithm etc., it ensure that after being compressed to desktop picture with preferable reconstruction quality, but its compression ratio is high not as Lossy Compression Algorithm, for to rebuilding the not high desktop picture of quality requirement according to lossless compression algorithm, it may appear that compression efficiency
The situation of reduction.
Therefore, Image Compression of the prior art Shortcomings in terms of compression efficiency and reconstruction quality is taken into account.The content of the invention is the invention provides a kind of method for compressing image and image processing apparatus, to take into account requirement during compression of images to compression efficiency and image reconstruction quality.
The first aspect of the invention is to provide a kind of method for compressing image, including：
Original image is divided at least one image block；
The quantity for the color category that view data corresponding to each image block is included judges；Quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed；
Quantity for color category is more than the image block of the first threshold, is compressed using Lossy Compression Algorithm, the code stream after being compressed；
Code stream after at least one described image block is compressed respectively merges into unified code stream；And the unified code stream is sent to client.
With reference to the method for compressing image of one side, in the first possible implementation, methods described also includes：
If the original image is the view data of RGB RGB color, the view data of the RGB color is converted to the view data of YUV color spaces；
Correspondingly, the color category included to the corresponding view data of each image block quantity carry out judge be specially：
The quantity for the color category that the view data of YUV color spaces corresponding to each image block is included judges.
With reference to the first possible implementation of one side, in second of possible implementation, the quantity for the color category that the view data of the YUV color spaces corresponding to each image block is included judge be specially：
Obtain the histogram information of the view data of the corresponding RGB color of each image block；According to the histogram information of each image block, the quantity of the color category of the view data of each image block is judged.
With reference to the first possible implementation of one side, in the third possible implementation, the quantity for color category be more than the first threshold image block, using Lossy Compression Algorithm be compressed including：
Quantity for color category is more than the first threshold, and less than the image block of Second Threshold, is compressed using the Lossy Compression Algorithm of the first quantization step, and the Second Threshold is more than the first threshold；
Quantity for color category is more than or equal to the image block of the Second Threshold, is compressed using the Lossy Compression Algorithm of the second quantization step, and second quantization step is more than first quantization step.
With reference to the first possible implementation of one side, in the 4th kind of possible implementation, the quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed is specially：
The quantity of color category is less than or equal to view data of the image block in RGB color of the first threshold, red R component data flow, green G component datas stream and blue B component data flow is decomposed into；
Using lossless compression algorithm, the R component data flow, the G component datas stream and the B component data flow are compressed respectively；
By the R component data flow after compression, G component datas stream and B component data stream merging, the code stream after being compressed.
The second aspect of the invention is to provide a kind of image processing apparatus, including：
Division unit, for original image to be divided into at least one image block；
Processing unit, the quantity of the color category for being included to the corresponding view data of each image block judges；Quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed；Quantity for color category is more than the image block of the first threshold, is compressed using Lossy Compression Algorithm, the code stream after being compressed；Transmitting element, at least one described image block to be compressed respectively after code stream merge into unified code stream, and the unified code stream is sent to client.
With reference to the image processing apparatus of second aspect, in the first possible implementation, described image processing unit also includes：
Converting unit, in the view data that the original image is RGB RGB color spaces
When, the view data of the RGB color is converted to the view data of YUV color spaces；Correspondingly, the processing unit specifically for：
The quantity for the color category that the view data of YUV color spaces corresponding to each image block is included judges.
With reference to the first possible implementation of second aspect, in second of possible implementation, the processing unit specifically for：
Obtain the histogram information of the view data of the corresponding RGB color of each image block；According to the histogram information of each image block, the quantity of the color category of the view data of each image block is judged.
With reference to the first possible implementation of second aspect, in the third possible implementation, the processing unit is additionally operable to：
Quantity for color category is more than the first threshold, and less than the image block of Second Threshold, is compressed using the Lossy Compression Algorithm of the first quantization step, and the Second Threshold is more than the first threshold；Quantity for color category is more than or equal to the image block of the Second Threshold, is compressed using the Lossy Compression Algorithm of the second quantization step, and second quantization step is more than first quantization step.
With reference to the first possible implementation of second aspect, in the 4th kind of possible implementation, the processing unit is additionally operable to：
The quantity of color category is less than or equal to view data of the image block in RGB color of the first threshold, red R component data flow, green G component datas stream and blue B component data flow is decomposed into；Using lossless compression algorithm, the R component data flow, the G component datas stream and the B component data flow are compressed respectively；R component data flow after compression, G component datas stream and B component datas stream are merged, the code stream after being compressed.
The third aspect of the invention is to provide a kind of image processing apparatus, including processor, memory, bus and communication interface；The memory is used to store computer executed instructions, the processor is connected with the memory by the bus, when described image processing unit is run, the computer executed instructions of memory storage described in the computing device so that described image processing unit performs above-mentioned method for compressing image.
4th aspect of the invention is to provide a kind of computer-readable medium, including computer executed instructions, so that during computer executed instructions, the computer performs above-mentioned figure described in the computing device of computer
As compression method.
Method for compressing image and image processing apparatus provided in an embodiment of the present invention, original image is divided into one or more image blocks, the quantity of color category according to included in image block determines the compression algorithm for needing to use, quantity to color category is less than or equal to the image block of first threshold, it is compressed using the preferable lossless compression algorithm of image reconstruction quality, quantity to color category is more than the image block of first threshold, it is compressed using the higher Lossy Compression Algorithm of compression efficiency, it will respectively obtain and unified code stream merged into the code stream after each tile compression, and unified code stream is sent to client.Illustrate the flow chart that Fig. 1 is the embodiment of method for compressing image one provided in an embodiment of the present invention；
Fig. 2 is the flow chart of another method for compressing image provided in an embodiment of the present invention；
Fig. 3 is the flow chart of another method for compressing image provided in an embodiment of the present invention；
Fig. 4 is the structural representation of image processing apparatus provided in an embodiment of the present invention；
Fig. 5 is the structural representation of another image processing apparatus provided in an embodiment of the present invention；Fig. 6 is the structural representation of another image processing apparatus provided in an embodiment of the present invention.The application scenarios of embodiment various embodiments of the present invention are mainly, the desktop picture of client remote shared server, the desktop picture of server is referred to as computer screen image, image processing apparatus described in various embodiments of the present invention can be the functional module in the server, or the server.
, it is necessary to first be encoded to desktop picture before desktop picture is sent to client by image processing apparatus, that is, desktop picture is compressed.Include that JPEG is serial, H.26X series and dynamic image expert group (Moving Pictures Experts Group/Mo tin Pictures Experts Group to the compression standard of natural image and video, M PEG-X) Lossy Compression Algorithm such as series, it is sensitivity characteristic and the continuous feature of natural image tone based on human vision and formulates；The lossless compression algorithms such as REL algorithms and lzw algorithm are included to the compression standard of text.
Because Lossy Compression Algorithm is higher than the compression ratio of lossless compression algorithm, correspondingly, when client is rebuild by decoding to image, the image compressed by Lossy Compression Algorithm there may be a greater degree of distortion than the image compressed by lossless compression algorithm.But be due to natural image color information enrich, texture is more smooth, and human eye is relatively low to the decoding Quality of recovery of natural image, though exist part lose
True man's eye, which there will not be, significantly to be discovered, therefore is that can be achieved to be effectively compressed natural image using Lossy Compression Algorithm.Natural image is compressed according to lossless compression algorithm, compression efficiency can be reduced on the contrary；But word is compressed according to Lossy Compression Algorithm, definition when can cause the client to reduce word is relatively low.
Lossy Compression Algorithm is suitable for the compression carried out to the natural image in desktop picture, and lossless compression algorithm is suitable for the compression to the text in desktop picture and figure progress.And in desktop picture not only include natural image, it is also possible to comprising substantial amounts of text and figure, if therefore desktop picture is compressed only with Lossy Compression Algorithm, the reconstruction quality of desktop picture can be caused poor；If being compressed only with lossless compression algorithm to desktop picture, the compression efficiency being compressed to desktop picture can be caused relatively low.
Lossy Compression Algorithm and lossless compression algorithm are combined in the method being compressed in various embodiments of the present invention to desktop picture, to take into account the compression efficiency being compressed to desktop picture and reconstruction quality.
Fig. 1 is the flow chart of the embodiment of method for compressing image one provided in an embodiment of the present invention, as shown in figure 1, this method includes：
101st, original image is divided at least one image block.
Specifically, its desktop picture is sent to each client by image processing apparatus when giving one or more clients by its Desktop Share；Before transmitting, image processing apparatus needs that the original image of desktop picture first is carried out into coding compression, and the original image after compression is sent into client.Client is after the original image after receiving the compression, according to the communication protocol between image processing apparatus and client, after being decoded to the original image of coding compression, you can restore the original image of image processing apparatus.
Method for compressing image is that each two field picture being directed in original image is carried out in various embodiments of the present invention, and the original image that image processing apparatus is sent to client can be the frame or multiple image after compression.
During actual share desktop, what image processing apparatus was sent to client is continuous multiple image, mode of the image processing apparatus to the coding compression of each frame original image, and the mode that the decoding of each frame original image of the client to receiving is decompressed, it can use the implementation in various embodiments of the present invention.
Image processing apparatus can carry out coding compression when carrying out coding compression to original image to whole original image subregion.Original image is divided into one or more image blocks.
For the ease of processing, for the original image of standard, the size of the image-region of each image block marked off is equal；For off-gauge original image, the method that color edges polishing can be used, to cause the image-region of each image block that there is equal size.It is understood that it is only a kind of preferred implementation that original image is divided into equal-sized image block, if original image is divided into the realization that the unequal image block of size has no effect on various embodiments of the present invention methods described.The size of each image-region specifically divided can be configured as needed.If the requirement to the reconstruction quality of original image is higher, and the requirement to compression efficiency is not high, and original image can be divided into less image block；If to the less demanding of the reconstruction quality of original image, but the requirement to compression efficiency is higher, and original image can be divided into larger image block；Specifically original image can be divided into according to the balance to reconstruction quality and compression efficiency by appropriately sized image-region.
102nd, the quantity of the color category included to the corresponding view data of each image block judges.
Specifically, original image after one or more image blocks are divided into by image processing apparatus, coding compression is carried out successively to each image block of original image.It is the quantity for the color category for obtaining each image block first when carrying out coding compression to each image block, according to the difference of color category, respectively to image block using corresponding coding compress mode.
First threshold is previously provided with image processing apparatus, using the first threshold as basic Rule of judgment, to judge whether image block is image block based on word or figure.
If the quantity of the color category of image block is less than or equal to the first threshold, illustrate that the picture material of the image block based on word or figure, to the image block of the type, is handled in the way of described in step 103；If the quantity of the color category of image block is more than the first threshold, illustrate the picture material of the image block not based on word or figure, to the image block of the type, by being handled described in step 104 in the way of.
103rd, the quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed.
If specifically, the quantity of the color category of image block is less than or equal to the first threshold, judging the picture material of the image block based on text or figure, the image block of the type being referred to as into text or graph data block below.
For text or graph data block, it is necessary to carry out coding compression using lossless compression algorithm.
104th, the quantity for color category is more than the image block of the first threshold, using damaging pressure
Compression algorithm is compressed, the code stream after being compressed.
Specifically, if the quantity of the color category of image block is more than the first threshold, the picture material of the image block is judged not based on text or figure, and may be the image block based on natural image, or both to include text or figure, the image block of natural image is included again.The image block based on natural image is referred to as natural image data block below, will both include text or figure, the image block including natural image is referred to as blended image data block again.
For natural image data block and blended image data block, coding compression can be carried out using Lossy Compression Algorithm.
105th, the code stream after at least one described image block is compressed respectively merges into unified code stream；And the unified code stream is sent to client.
Image processing apparatus carries out coding compression to each image block of original image respectively according to above-mentioned steps.After the coding compression to each image block is completed, the data flow after all images block is encoded is synthesized, and forms unified code stream, and regard the unified code stream of synthesis as the code stream after the compression of the desktop picture.
Image processing apparatus exports the code stream after the compression of original image, is sent to client；Client is after the code stream is received, according to the communication protocol between the relevant information and image processing apparatus and client carried in code stream, the code stream is decoded, the image obtained after decoding is the desktop picture for the image processing apparatus that client is restored, so as to realize client to a frame of image processing apparatus or sharing for multiframe desktop picture.And then, when image processing apparatus continuously by compression after desktop picture be sent to client, client is correspondingly decoded to the code stream received, when restoring the corresponding image of code stream, that is, realizes client to the shared of the desktop of image processing apparatus.
Method for compressing image provided in an embodiment of the present invention, original image is divided into one or more image blocks, the quantity of color category according to included in image block determines the compression algorithm for needing to use, quantity to color category is less than or equal to the image block of first threshold, it is compressed using the preferable lossless compression algorithm of image reconstruction quality, quantity to color category is more than the image block of first threshold, it is compressed using the higher Lossy Compression Algorithm of compression efficiency, it will respectively obtain and unified code stream merged into the code stream after each tile compression, and unified code stream is sent to client.Due to the type of the amount field partial image block according to each image block color category, for different types of image block, coding compression is carried out using Lossy Compression Algorithm or damage compression algorithm, the reconstruction quality and compression efficiency to desktop picture can effectively be taken into account, and compared with only with the mode of single compression algorithm, with more preferable reconstruction quality, more
Big compression ratio；Further, since careful classification need not be carried out to the different type of image block, it is only necessary to use broad classification mode, therefore with relatively low computation complexity, enable to Desktop Share that there is preferable real-time.
Fig. 2 is the flow chart of another method for compressing image provided in an embodiment of the present invention, as shown in Fig. 2 this method can also include：
201st, original image is divided at least one image block.
Specifically, may refer to the implementation described in step 101.
202nd, the quantity of the color category included to the corresponding view data of each image block judges.
Specifically, may refer to the implementation described in step 102.
Further, image processing apparatus judges that the method for the quantity for the color category that the corresponding view data of image block is included can be：
Obtain the corresponding RGB of each image block（Red Green Blue, RGB) color space view data histogram information；According to the histogram information of each image block, the quantity of the color category of the view data of each image block is judged.
It is that the pixel to image block is scanned to obtain histogrammic method, color number is recorded respectively, R, G, the span of B component are 0-255, so as to obtain the histogram of the image block.
Correspondingly, before step 202 is performed, if the original image is the view data of RGB color, the view data of the RGB color is converted into lightness colourity（YUV) the view data of color space.Wherein, YUV can also be referred to as YCrCb;Y represents lightness (Luminance or Luma), i.e. grey decision-making；U and V represent colourity (Chrominance or Chroma).
And then the quantity of the color category included to the view data of the corresponding RGB color of each image block judges.
The operating procedure of the specific view data that the view data of RGB color is converted to YUV color spaces needs to carry out before performing 202.In addition, carrying out the conversion of the color space of view data, it can carry out, can also respectively be carried out for each image block after being divided to original image before being divided to original image.
Image processing apparatus is after the conversion to the color space of view data is completed, and corresponding view data has the view data and the picture number in YUV color spaces in RGB color respectively
According to.No matter the conversion to color space and sequencing to being performed between the division of original image, obtain one or more image blocks, each image block has the view data and the view data in YUV color spaces in RGB color respectively.
203rd, the quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed.
Specifically, may refer to the implementation described in step 103.
In addition, because lossless compression algorithm needs the view data for image block in RGB color to carry out coding compression, therefore, further, the quantity of color category can be less than or equal to view data of the image block in RGB color of the first threshold, red R component data flow, green G component datas stream and blue B component data flow is decomposed into；Using lossless compression algorithm, the R component data flow, the G component datas stream and the B component data flow are compressed respectively；By R component datas stream, G component datas stream and the B component data stream merging after compression, the code stream after being compressed.
204th, the quantity for color category is more than the first threshold, and less than the image block of Second Threshold, is compressed using the Lossy Compression Algorithm of the first quantization step.
Wherein, the Second Threshold is more than the first threshold.
205th, the quantity for color category is more than or equal to the image block of the Second Threshold, is compressed using the Lossy Compression Algorithm of the second quantization step.
Wherein, second quantization step is more than first quantization step.
Specifically, Lossy Compression Algorithm needs the view data for YUV color spaces to carry out coding compression.In Lossy Compression Algorithm, by setting the numerical values recited of quantization step, different compression effectiveness are correspondingly realized.The numerical value of quantization step is bigger, then higher to the compression ratio of view data, correspondingly reconstruction quality will be lower, and compression efficiency is higher；The numerical value of quantization step is smaller, then the compression to view data is smaller, and correspondingly reconstruction quality will be higher, and compression efficiency is relatively low.
Quantity for color category is more than the image block of first threshold, can further divide into natural image data block and blended image data block.In image processing apparatus in addition to being preset with first threshold, Second Threshold can also be set with, the numerical value of the Second Threshold is more than the numerical value of first threshold.Because the natural image included in image block is more, text or figure are fewer, then the quantity of its color category is more, otherwise similarly, the natural image included in image block is fewer, and text or figure are more, then the quantity of its color category is fewer.Therefore, if the quantity of the color category of image block is more than first threshold, but Second Threshold is less than, then judges the image block as blended image data block；If the color of image block
The quantity of species is more than or equal to Second Threshold, then judges the image block as natural image data block.Image processing apparatus carries out coding compression to the blended image data block judged using the Lossy Compression Algorithm of the first quantization step；To the natural image data block judged, coding compression is carried out using the Lossy Compression Algorithm of the second quantization step.Wherein, the numerical value of the second quantization step is more than the numerical value of the first quantization step.Generally, the span of quantization step is 1-100.Therefore, the compression ratio being compressed to natural image data block is larger, and compression efficiency is of a relatively high, and the reconstruction quality of image is relatively low；The compression being compressed to blended image data block is smaller, and compression efficiency is relatively low, and the reconstruction quality of image is of a relatively high.
The numerical value smaller than the quantization step being compressed to natural image data block will be set to the quantization step that blended image data block is compressed, the image reconstruction quality being compressed to blended image data block can be improved, to improve the definition of word or figure when being reduced by client in blended image data block.
206th, the code stream after at least one described image block is compressed respectively merges into unified code stream；And the unified code stream is sent to client.
Specifically, may refer to the implementation described in step 105.
Method for compressing image provided in an embodiment of the present invention, because each image block is respectively provided with the image information of two kinds of color spaces, make it possible to carry out coding compression using lossless compression algorithm for text or graph data block, coding compression is carried out using the Lossy Compression Algorithm of larger quantization step to natural image data block, coding compression is carried out using the Lossy Compression Algorithm of small amount step-length for blended image data block, enable the word in blended image data block that there is higher definition when rebuilding, the reconstruction quality and compression efficiency to desktop picture can also effectively be taken into account, and compared with only with the mode of single compression algorithm, with more preferable reconstruction quality, bigger compression ratio；Further, since careful classification need not be carried out to the different type of image block, it is only necessary to use broad classification mode, therefore with relatively low computation complexity, enable to Desktop Share that there is preferable real-time.
Fig. 3 is the flow chart of another method for compressing image provided in an embodiment of the present invention, in order to carry out real-time efficient coding to desktop picture, different qualities of the embodiment of the present invention according to desktop picture Chinese version, figure and natural image on color and texture, it is proposed that the overall procedure of coding method as shown in Figure 3.Executive agent in the embodiment of the present invention is above-mentioned server images processing unit.
Step 301, acquisition desktop picture.
Step 302, desktop picture by RGB color is transformed into YUV color spaces.
It should be noted that RGB color and yuv space are only the citing of two kinds of color spaces, optional color space is not limited to that.
Because lossless compression algorithm is needed to use in the view data of RGB color, Lossy Compression Algorithm is needed to use in the view data of YUV color spaces.Therefore, in embodiments of the present invention while the view data of RGB color is retained, the view data of RGB color is also converted to the view data of YUV color spaces, so that desktop picture has two parts of view data in two kinds of color spaces.
Step 303, the image block that desktop picture is divided into multiple 16 X 16.
When desktop picture is divided into image block, the image block of the sizes of 16 x 16 can be divided into, 32 x 32 or the image block of the sizes of 8 x 8 or other sizes can also be divided into.If each image block divided is larger, the compression efficiency for encoding compression is higher, and reconstruction quality may be relatively low；If each image block divided is smaller, compression efficiency during coding compression is relatively low, and reconstruction quality may be higher.Therefore, for the setting of the size of image block divided, the requirement depending on reality to compression efficiency and reconstruction quality, 16 X 16 tile size is a kind of preferred implementation.
For off-gauge desktop picture, the method that can use color edges polishing is unsatisfactory for dividing the image-region of size by mending the mode such as 0, so that the size all same of the image block obtained during to dividing.
After one or more image blocks of desktop picture are obtained, the quantity of the color category of each image block is further obtained.Which type that each image block belongs in text or graph data block, natural image data block or blended image data block is judged according to the quantity of color category.
Specifically, obtaining the method for the quantity of the color category of image block can be, according to histogram information of the image block in RGB color spaces, the quantity of the color category of image block is obtained.
The color category of image block is judged using histogram information, is that the negligible amounts of color category in its histogram information, histogrammic distribution is in discrete because the color of generally image block based on text or figure is simple, texture variations are more violent；And the rich color of the image block based on natural image, the more flat Slow of texture variations, the quantity of color category in its histogram information is more, and histogrammic distribution is in continuous state, so can simply and efficiently distinguish the general type of image block using histogram information.
Setting first threshold T1 and Second Threshold T2, T1 and T2 are respectively the amount threshold of two color categories, and T1 is less than T2.For the image block simply based on text or figure, the quantity Num of the color category image blocks for being less than or equal to T1 are determined as text or graph data block by the quantity of its color category not over T1；Image block for including more text or figure, the quantity of its color category
Typically not over T2, therefore the quantity Num of the color category image blocks for being more than or equal to T2 are determined as natural image data block；It is more than T1 for the quantity Num of color category and is less than T2 image block, can be roughly determined as blended image data block.Although such mode classification is more rough, higher compression efficiency can guarantee that.
Wherein, T1 and T2 numerical value can be configured as needed.One kind is preferable to provide mode, and T1 is set into 6, and T2 is set into 20, and this set-up mode is only a kind of for example, optional set-up mode is not limited to that.
If step 304, image block are text or graph data block, lossless compression-encoding mode is used to RGB color.
Because text or graph data block have strong edge and shape facility, human eye requires higher to text/graphics information sensing to its decoding Quality of recovery, thus lossless compression method is optimal selection.Common lossless compression algorithm, such as LZ W are encoded（Encoding) algorithm, RLE algorithms and Run- Length Coding etc..These compression algorithms are required for being encoded in the view data of RGB color.
To improve compression ratio, R, G, B component in rgb space are compressed respectively, the compressed bit stream of the compressed bit stream, the compressed bit stream of G components and B component of R components is formed.Due to each 1, G, B component data between 0-255, the input requirements using many algorithms such as RLE, LZW can be met, while can also lift compression ratio.The compressed bit stream of the compressed bit stream of R component, the compressed bit stream of G components and B component is synthesized into the mixed code stream after compression, that is, completes the compression to text or video data block.For the mixed code stream, client is decoded as 1, G, B component respectively when being decoded according to code stream order, and then restores the view data of RGB color, completes the reconstruction to text or video data block.
If step 305, image block are natural image data block, to YUV color spaces using high compression rate based on intraframe predictive coding H.264.
Because the color information of natural image is enriched, texture is smoother, human eye is relatively low to the decoding Quality of recovery of natural image, perceives greatly very much even if there is partial distortion human eye there will not be, thus uses Lossy Compression Algorithm to realize effective compression natural image data block.
The present invention is used based on intraframe predictive coding H.264 to the view data of the yuv space of natural image data block, or similar encryption algorithm H.264,16 X 16,8 X 8 and 4 X, 4 three kinds of intra-frame encoding modes can be used to luminance component, each pattern can also be using 9 kinds of prediction directions；The intra-prediction code modes of 8 x 8 can be used for color difference components, each pattern can also use four kinds
Prediction direction；And then the Variable Length Code algorithm based on context-adaptive is used, carry out entropy code.By using the method for increasing quantization step, increasing compression ratio reduces picture quality, it is ensured that the high compression ratio of entire image.
If step 306, image block are blended image data block, to YUV color spaces using little compressible based on intraframe predictive coding H.264.
Due to both may also include natural image, therefore the view data of the yuv space to blended image data block comprising text or figure in blended image data block, it can use based on intraframe predictive coding H.264, or similar encryption algorithm H.264.The distortion factor of decoding image is controlled by quantization step, approximate Lossless Compression is generally realized using lower quantization step-length.So as to simply and effectively realize the compressed encoding to blended image data block.
Step 307, the unified code stream output of formation.
Finally, the code stream after the compression of each image block of whole desktop picture is merged into unified code stream output.The unified code stream of formation is sent to after client, client is decoded according to communication protocol according to code stream order, so as to restore the desktop picture of image processing apparatus in client.
Method for compressing image provided in an embodiment of the present invention, desktop picture is transformed into YUV color spaces by RGB color, desktop picture is divided into the non-overlapped image block of the sizes of 16 x 16, according to the color and textural characteristics of each image block, image block is divided into text or graph data block, blended image data block or the class of natural image data block three, lossless compression-encoding mode is used in original RGB spaces to text or graph data block, the lossy coding mode for being similar to H.264 infra-frame prediction is used to natural image data block, to mixed block also using similar to H.264 intraframe predictive coding, but in order to ensure more preferable reconstruction quality, using the quantization step smaller than natural image data block, that is the more parameter of high compression quality.No matter in terms of the compression efficiency or in terms of reconstruction quality, the method for compressing image in the embodiment of the present invention is superior to single use JPEG, JPEG2000, JPEG-LS, method for compressing image traditional LZW；And because the method for compressing image in the embodiment of the present invention is relatively simple to the classification of image, the complexity of calculating can be effectively reduced, the application of class is shared to desktop, it is ensured that more preferable real-time.
In addition, utilizing graphic user interface（Graphical User Interface, GUI) instruction capture desktop picture data are carried out in the method for Desktop Share, when the operation for involving the need for being compressed image, the method in above-described embodiment can also be used, for different types of image, coding compression is carried out using lossless compression algorithm or Lossy Compression Algorithm.
Specifically, using GUI instruct capture images data mode be, at server images processing unit end, extension shows driving function, in operating system drive layer capture GUI instructions, instruction and related data are received after director data directly or through client, client is delivered to after compression, recall operation system, which is reappeared, draws, so that the desktop of far-end server image processing apparatus is reconstructed into client.
In order to further reduce instruction and data amount, generally GUI instruction and datas are compressed using lossless compression algorithm.It is all to be widely used because data volume is much smaller compared with the method for direct copying screen using the method for capture GUI instructions.It is most typical such as, the operating system Windows Server of Microsoft provide Remote desk process function, its RDP used（Remote Desktop Protocol, RDP) agreement, employ and capture GUI instruction methods in operating system aspect, then compressed by director data, image is repainted in client.Si Jie companies desktop protocol, which equally employs GUI instruction methods, realizes efficient desktop.
Instructed using GUI and realize that the method for computer screen image transmission needs to realize based on particular platform, in the method for involve the need for being compressed image operation when, the method in above-described embodiment can also be used, equally certain balance can be reached in terms of the compression efficiency and reconstruction quality of compression of images.
Fig. 4 is the structural representation of image processing apparatus provided in an embodiment of the present invention, as shown in figure 4, the image processing apparatus includes division unit 11, processing unit 12 and transmitting element 13.
Division unit 11, for original image to be divided into at least one image block；
Processing unit 12, the quantity of the color category for being included to the corresponding view data of each image block judges；Quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed；Quantity for color category is more than the image block of the first threshold, is compressed using Lossy Compression Algorithm, the code stream after being compressed；Transmitting element 13, at least one described image block to be compressed respectively after code stream merge into system-code stream, and the unified code stream is sent to client.
Specifically, the method that image processing apparatus carries out compression of images, may refer to the operating procedure described in above-mentioned corresponding embodiment of the method, here is omitted.
Image processing apparatus provided in an embodiment of the present invention, original image is divided into one or more image blocks, the quantity of color category according to included in image block determines the compression algorithm for needing to use, quantity to color category is less than or equal to the image block of first threshold, preferably lossless using image reconstruction quality
Compression algorithm is compressed, quantity to color category is more than the image block of first threshold, it is compressed using the higher Lossy Compression Algorithm of compression efficiency, will respectively obtains and unified code stream is merged into the code stream after each tile compression, and unified code stream is sent to client.Due to the type of the amount field partial image block according to each image block color category, for different types of image block, coding compression is carried out using Lossy Compression Algorithm or damage compression algorithm, the reconstruction quality and compression efficiency to desktop picture can effectively be taken into account, and compared with only with the mode of single compression algorithm, with more preferable reconstruction quality, bigger compression ratio；Further, since careful classification need not be carried out to the different type of image block, it is only necessary to use broad classification mode, therefore with relatively low computation complexity, enable to Desktop Share that there is preferable real-time.
Fig. 5 is the structural representation of another image processing apparatus provided in an embodiment of the present invention, and as shown in Fig. 5, the image processing apparatus can also include converting unit 14.
Converting unit 14, for when the original image is the view data of RGB RGB color, the view data of the RGB color to be converted to the view data of YUV color spaces；Correspondingly, the processing unit 12 specifically for：
The quantity for the color category that the view data of YUV color spaces corresponding to each image block is included judges.
Further, the processing unit 12 can be also used for：
Obtain the histogram information of the view data of the corresponding RGB color of each image block；According to the histogram information of each image block, the quantity of the color category of the view data of each image block is judged.
Further, the processing unit 12 can be also used for：
Quantity for color category is more than the first threshold, and less than the image block of Second Threshold, is compressed using the Lossy Compression Algorithm of the first quantization step, and the Second Threshold is more than the first threshold；Quantity for color category is more than or equal to the image block of the Second Threshold, is compressed using the Lossy Compression Algorithm of the second quantization step, and second quantization step is more than first quantization step.
Further, the processing unit 12 can be also used for：
The quantity of color category is less than or equal to view data of the image block in RGB color of the first threshold, red R component data flow, green G component datas stream and blue B component data flow is decomposed into；Using lossless compression algorithm, respectively to the R component data flow, the G component datas stream and institute
B component data flow is stated to be compressed；R component data flow after compression, G component datas stream and B component datas stream are merged, the code stream after being compressed.
Specifically, the method that image processing apparatus carries out compression of images, may refer to the operating procedure described in above-mentioned corresponding embodiment of the method, here is omitted.
Image processing apparatus provided in an embodiment of the present invention, because each image block is respectively provided with the image information of two kinds of color spaces, make it possible to carry out coding compression using lossless compression algorithm for text or graph data block, coding compression is carried out using the Lossy Compression Algorithm of larger quantization step to natural image data block, coding compression is carried out using the Lossy Compression Algorithm of small amount step-length for blended image data block, enable the word in blended image data block that there is higher definition when rebuilding, the reconstruction quality and compression efficiency to desktop picture can also effectively be taken into account, and compared with only with the mode of single compression algorithm, with more preferable reconstruction quality, bigger compression ratio；Further, since careful classification need not be carried out to the different type of image block, it is only necessary to use broad classification mode, therefore with relatively low computation complexity, enable to Desktop Share that there is preferable real-time.
Fig. 6 is the structural representation of another image processing apparatus provided in an embodiment of the present invention, and as shown in Fig. 6, the image processing apparatus includes：Processor 21, memory 22, bus 23 and communication interface 24.Connected between processor 21, memory 22 and communication interface 24 by bus 23 and complete mutual communication.
Processor 21 may be monokaryon or multinuclear CPU（Central Processing Unit, CPU), or be specific integrated circuit（Application Specific Integrated Circuit, abbreviation ASIC), or to be configured to implement one or more integrated circuits of the embodiment of the present invention.Memory 22 can be high-speed RAM memory, or nonvolatile memory（Non-volatile memory), for example, at least one disk deposits 4 all devices.
Memory 22 is used to deposit program 221.Specifically, can include program code in program 221, described program code includes computer executed instructions.
When described image processing unit is run, the operation program 221 of processor 21, to perform：Original image is divided at least one image block；
The quantity for the color category that view data corresponding to each image block is included judges；Quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed；
Quantity for color category is more than the image block of the first threshold, using Lossy Compression Algorithm
It is compressed, the code stream after being compressed；
Code stream after at least one described image block is compressed respectively merges into unified code stream；And the unified code stream is sent to client.
Specifically, the method that image processing apparatus carries out compression of images, the operating procedure described in above-mentioned corresponding embodiment of the method is may refer to, here is omitted, and be achieved in the goal of the invention of the requirement when embodiment of the present invention takes into account compression of images to compression efficiency and image reconstruction quality.
The embodiment of the present invention also provides a kind of computer-readable medium, including above computer execute instruction, so that during computer executed instructions, the computer performs the method for compressing image in the various embodiments described above described in the computing device of computer.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above method embodiment can be completed by the related hardware of programmed instruction, foregoing program can be stored in a computer read/write memory medium, the program upon execution, performs the step of including above method embodiment；And foregoing storage medium includes：ROM, RAM, magnetic disc or CD etc. are various can be with the medium of store program codes.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although the present invention is described in detail with reference to foregoing embodiments, it will be understood by those within the art that：It can still modify to the technical scheme described in foregoing embodiments, or carry out equivalent substitution to which part or all technical characteristic；And these modifications or replacement, the essence of appropriate technical solution is departed from the scope of various embodiments of the present invention technical scheme.
Claims (12)
- Claims1st, a kind of method for compressing image, it is characterised in that including：Original image is divided at least one image block；The quantity for the color category that view data corresponding to each image block is included judges；Quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed；Quantity for color category is more than the image block of the first threshold, is compressed using Lossy Compression Algorithm, the code stream after being compressed；Code stream after at least one described image block is compressed respectively merges into unified code stream；And the unified code stream is sent to client.2nd, method for compressing image according to claim 1, it is characterised in that methods described also includes：If the original image is the view data of RGB RGB color, the view data of the RGB color is converted to the view data of YUV color spaces；Correspondingly, the quantity of the color category included to the corresponding view data of each image block, which carries out judgement, includes：The quantity for the color category that the view data of YUV color spaces corresponding to each image block is included judges.3rd, method for compressing image according to claim 2, it is characterised in that the quantity for the color category that the view data of the YUV color spaces corresponding to each image block is included, which carries out judgement, to be included：Obtain the histogram information of the view data of the corresponding RGB color of each image block；According to the histogram information of each image block, the quantity of the color category of the view data of each image block is judged.4th, method for compressing image according to claim 2, it is characterised in that the quantity for color category be more than the first threshold image block, using Lossy Compression Algorithm be compressed including：Quantity for color category is more than the first threshold, and less than the image block of Second Threshold, is compressed using the Lossy Compression Algorithm of the first quantization step, and the Second Threshold is more than the first threshold； Quantity for color category is more than or equal to the image block of the Second Threshold, is compressed using the Lossy Compression Algorithm of the second quantization step, and second quantization step is more than first quantization step.5th, method for compressing image according to claim 2, it is characterised in that the quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed is specially：The quantity of color category is less than or equal to view data of the image block in RGB color of the first threshold, red R component data flow, green G component datas stream and blue B component data flow is decomposed into;Using lossless compression algorithm, the R component data flow, the G component datas stream and the B component data flow are compressed respectively；By the R component data flow after compression, G component datas stream and B component data stream merging, the code stream after being compressed.6th, a kind of image processing apparatus, it is characterised in that including：Division unit, for original image to be divided into at least one image block；Processing unit, the quantity of the color category for being included to the corresponding view data of each image block judges；Quantity for color category is less than or equal to the image block of first threshold, is compressed using lossless compression algorithm, the code stream after being compressed；Quantity for color category is more than the image block of the first threshold, is compressed using Lossy Compression Algorithm, the code stream after being compressed；Transmitting element, at least one described image block to be compressed respectively after code stream merge into unified code stream, and the unified code stream is sent to client.7th, image processing apparatus according to claim 6, it is characterised in that described image processing unit also includes：Converting unit, for when the original image is the view data of RGB RGB color spaces, the view data of the RGB color to be converted to the view data of YUV color spaces；Correspondingly, the processing unit specifically for：The quantity for the color category that the view data of YUV color spaces corresponding to each image block is included judges.8th, image processing apparatus according to claim 7, it is characterised in that the processing unit specifically for： Obtain the histogram information of the view data of the corresponding RGB color of each image block；According to the histogram information of each image block, the quantity of the color category of the view data of each image block is judged.9th, image processing apparatus according to claim 7, it is characterised in that the processing unit is additionally operable to：Quantity for color category is more than the first threshold, and less than the image block of Second Threshold, is compressed using the Lossy Compression Algorithm of the first quantization step, and the Second Threshold is more than the first threshold；Quantity for color category is more than or equal to the image block of the Second Threshold, is compressed using the Lossy Compression Algorithm of the second quantization step, and second quantization step is more than first quantization step.10th, image processing apparatus according to claim 7, it is characterised in that the processing unit is additionally operable to：The quantity of color category is less than or equal to view data of the image block in RGB color of the first threshold, red R component data flow, green G component datas stream and blue B component data flow is decomposed into；Using lossless compression algorithm, the R component data flow, the G component datas stream and the B component data flow are compressed respectively；R component data flow after compression, G component datas stream and B component datas stream are merged, the code stream after being compressed.11st, a kind of image processing apparatus, it is characterised in that including processor, memory, bus and communication interface；The memory is used to store computer executed instructions, the processor is connected with the memory by the bus, when described image processing unit is run, the computer executed instructions of memory storage described in the computing device so that described image processing unit performs the method for compressing image as described in any in claim 1-5.12nd, a kind of computer-readable medium, it is characterised in that including computer executed instructions, so that during computer executed instructions, the computer performs the method for compressing image as described in any in claim 1-5 described in the computing device of computer.
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